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Vamshidhar Singh

@vamshidharsingh

Forward Deployed Engineer, 6+ years shipping LangGraph agents, RAG and FastAPI services to production for banking, retail and logistics clients

United States

Message

What I'm looking for

Looking for a Forward Deployed Engineer or Applied AI Engineer role: working directly with customers to scope problems, then shipping LLM agents, RAG, APIs and data integrations to production. I like small teams with real ownership and I’m comfortable traveling or working on site with clients. Open to remote, hybrid or onsite across the US.

At Bank of America, I architected the LangGraph orchestration behind Erica, routing requests to specialized agents and raising intent resolution to 92%. I also built RAG pipelines that gave more than 40 analysts cited answers and made policy lookups 40% faster.

I fine-tuned Whisper/Conformer speech models and applied RLHF and RLVR so model answers follow bank policy and tone. I owned evaluation and guardrails, including regression suites and real-time PII redaction running at 99.8% accuracy.

At Tata Consultancy Services, I built recommendation, forecasting, retention, and spatial ML solutions for clients including Leroy Merlin, Creatrix Campus, and Hub Group. That work included models that lifted click-through rate by 22%, improved ETA accuracy by 25%, and saved Hub Group more than $400K a year in idle fuel.

Experience

Work history, roles, and key accomplishments

Current

AI/ML Engineer (Data Focus)

Current

Bank of America

Jun 2024 - Present (2 years 5 months)

Architected LLM orchestration for Erica, built RAG pipelines, fine-tuned speech models, and owned evaluation platform. Improved intent resolution to 92% and cut document lookup time by 40%.

Python Lang Chain LangGraph Pinecone ChromaDB RAG RLHF RLVR PyTorch Whisper Conformers Ragas DeepEval Langsmith fastAPI Docker Kubernetes gRPC Kafka SQL

Machine Learning Engineer

Tata Consultancy Services

Feb 2020 - Jul 2023 (3 years 5 months)

Built recommendation, forecasting, retention, NLP, spatial ML, and optimization models for clients across retail, education, logistics, and banking. Delivered measurable improvements in CTR, ETA accuracy, and cost savings.